Pinned Repositories
Authentication
camera_distance_measurement
Demo for estimating the height of a stair step
imagenet_localization
interactive_overlay
invert
PyTorch implementation of Mahendran & Vedaldi, 2015: "Understanding Deep Image Representations by Inverting Them"
net2vec
Code for Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks
perturb_explanations
Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"
pointing_game
pytorch-explain-black-box
PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation
pytorch_models
ruthcfong's Repositories
ruthcfong/perturb_explanations
Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"
ruthcfong/pointing_game
ruthcfong/pytorch_models
ruthcfong/imagenet_localization
ruthcfong/interactive_overlay
ruthcfong/TorchRay
Understanding Deep Networks via Extremal Perturbations and Smooth Masks
ruthcfong/ruthcfong.github.io
ruthcfong/pytorch_cifar
95.16% on CIFAR10 with PyTorch
ruthcfong/pytorch_workflow
ruthcfong/amplifyapp
Amplify Console CI / CD Demo
ruthcfong/bag-of-local-features-models
Pretrained bag-of-local-features neural networks
ruthcfong/bam
ruthcfong/chineseinflow-javascript
Practice Chinese characters
ruthcfong/CUB200-2011
The collection of 80*80-pixels bird-images from cub200-2011 dataset.
ruthcfong/cutout
2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552
ruthcfong/dropblock
Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.
ruthcfong/excitationbp
Visualizing how deep networks make decisions
ruthcfong/hydra
Hydra is a framework for elegantly configuring complex applications
ruthcfong/lucid
A collection of infrastructure and tools for research in neural network interpretability.
ruthcfong/mAP
mean Average Precision - This code evaluates the performance of your neural net for object recognition.
ruthcfong/MichiGAN
MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait Editing (SIGGRAPH 2020)
ruthcfong/NetDissect-Lite
Light version of Network Dissection for Quantifying Interpretability of Networks
ruthcfong/nifty-web-apps
Build a web app for any programming assignment.
ruthcfong/partialconv
A New Padding Scheme: Partial Convolution based Padding
ruthcfong/perturb_improvements
ruthcfong/post--example
Example Distill article repository—clone, rename, start writing!
ruthcfong/ProtoPNet
This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpretable Image Recognition" (to appear at NeurIPS 2019), by Chaofan Chen* (Duke University), Oscar Li* (Duke University), Chaofan Tao (Duke University), Alina Jade Barnett (Duke University), Jonathan Su (MIT Lincoln Laboratory), and Cynthia Rudin (Duke University) (* denotes equal contribution).
ruthcfong/revisiting-self-supervised
ruthcfong/saliency_sampler
The saliency-based is a distortion layer for convolutional neural networks that helps to improve the spatial sampling of input data for a given task.
ruthcfong/starter-hugo-academic
🎓 Hugo Academic Theme 创建一个学术网站. Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify.